package org.apache.lucene.search;

/**
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

import java.io.IOException;

import org.apache.lucene.index.TermDocs;

/** Expert: A <code>Scorer</code> for documents matching a <code>Term</code>.
 */
final class TermScorer extends Scorer {
    private final TermDocs termDocs;
    private final byte[] norms;
    private float weightValue;
    private int doc = -1;
    private int freq;

    private final int[] docs = new int[32]; // buffered doc numbers
    private final int[] freqs = new int[32]; // buffered term freqs
    private int pointer;
    private int pointerMax;

    private static final int SCORE_CACHE_SIZE = 32;
    private final float[] scoreCache = new float[SCORE_CACHE_SIZE];

    /**
     * Construct a <code>TermScorer</code>.
     * 
     * @param weight
     *          The weight of the <code>Term</code> in the query.
     * @param td
     *          An iterator over the documents matching the <code>Term</code>.
     * @param similarity
     *          The </code>Similarity</code> implementation to be used for score
     *          computations.
     * @param norms
     *          The field norms of the document fields for the <code>Term</code>.
     */
    TermScorer(Weight weight, TermDocs td, Similarity similarity, byte[] norms) {
        super(similarity, weight);

        this.termDocs = td;
        this.norms = norms;
        this.weightValue = weight.getValue();

        for (int i = 0; i < SCORE_CACHE_SIZE; i++)
            scoreCache[i] = getSimilarity().tf(i) * weightValue;
    }

    @Override
    public void score(Collector c) throws IOException {
        score(c, Integer.MAX_VALUE, nextDoc());
    }

    // firstDocID is ignored since nextDoc() sets 'doc'
    @Override
    protected boolean score(Collector c, int end, int firstDocID) throws IOException {
        c.setScorer(this);
        while (doc < end) { // for docs in window
            c.collect(doc); // collect score

            if (++pointer >= pointerMax) {
                pointerMax = termDocs.read(docs, freqs); // refill buffers
                if (pointerMax != 0) {
                    pointer = 0;
                } else {
                    termDocs.close(); // close stream
                    doc = Integer.MAX_VALUE; // set to sentinel value
                    return false;
                }
            }
            doc = docs[pointer];
            freq = freqs[pointer];
        }
        return true;
    }

    @Override
    public int docID() {
        return doc;
    }

    @Override
    public float freq() {
        return freq;
    }

    /**
     * Advances to the next document matching the query. <br>
     * The iterator over the matching documents is buffered using
     * {@link TermDocs#read(int[],int[])}.
     * 
     * @return the document matching the query or NO_MORE_DOCS if there are no more documents.
     */
    @Override
    public int nextDoc() throws IOException {
        pointer++;
        if (pointer >= pointerMax) {
            pointerMax = termDocs.read(docs, freqs); // refill buffer
            if (pointerMax != 0) {
                pointer = 0;
            } else {
                termDocs.close(); // close stream
                return doc = NO_MORE_DOCS;
            }
        }
        doc = docs[pointer];
        freq = freqs[pointer];
        return doc;
    }

    @Override
    public float score() {
        assert doc != -1;
        float raw = // compute tf(f)*weight
                        freq < SCORE_CACHE_SIZE // check cache
                                        ? scoreCache[freq] // cache hit
                                        : getSimilarity().tf(freq) * weightValue; // cache miss

        return norms == null ? raw : raw * getSimilarity().decodeNormValue(norms[doc]); // normalize for field
    }

    /**
     * Advances to the first match beyond the current whose document number is
     * greater than or equal to a given target. <br>
     * The implementation uses {@link TermDocs#skipTo(int)}.
     * 
     * @param target
     *          The target document number.
     * @return the matching document or NO_MORE_DOCS if none exist.
     */
    @Override
    public int advance(int target) throws IOException {
        // first scan in cache
        for (pointer++; pointer < pointerMax; pointer++) {
            if (docs[pointer] >= target) {
                freq = freqs[pointer];
                return doc = docs[pointer];
            }
        }

        // not found in cache, seek underlying stream
        boolean result = termDocs.skipTo(target);
        if (result) {
            pointerMax = 1;
            pointer = 0;
            docs[pointer] = doc = termDocs.doc();
            freqs[pointer] = freq = termDocs.freq();
        } else {
            doc = NO_MORE_DOCS;
        }
        return doc;
    }

    /** Returns a string representation of this <code>TermScorer</code>. */
    @Override
    public String toString() {
        return "scorer(" + weight + ")";
    }

}
